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Predictive Models for Dosimetry of the Organs-At-Risk in Interstitial Gynecologic Brachytherapy


A Damato

A Damato*, A Viswanathan, R Cormack, Brigham and Women's Hospital, Boston, MA

SU-E-T-340 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose:
In this work, mathematical models for the prediction of the D2cc of rectum and bladder in interstitial gynecologic brachytherapy based on geometric information, without the generation of a treatment plan, are discussed and validated.

Methods:
Previous plans were used to establish the relationship between D2cc and the overlapping volume of the organ-at-risk with the targeted area (C0) or a 1-cm expansion of the target area (C1). Three mathematical models were evaluated: D2cc = a*C1+b (LIN); D2cc = a - exp(-b*C0) (EXP); and a mixed approach (MIX), where both C0 and C1 were inputs of the model. The model's parameters were optimized on a training set, and the model predictive error (predicted D2cc - real D2cc) was calculated on a validation set. The data of 20 patients treated with interstitial gynecologic brachytherapy were used to perform a K-fold cross validation analysis, with K = 2, 4, 6 ,8, 10, and 20.

Results:
MIX was associated with the smallest mean prediction error with error <6.4% for an 18-patient training set; LIN had an error <8.5%; EXP had an error < 8.3%. Best-case-scenario analysis showed that an error <5% could be achieved for a 10-patient training set with MIX, error <7.5% for LIN and error <7.0% for EXP. The error decreases with the increase in training set size, with the most marked decrease observed for MIX.

Conclusion:
Ten training cases allow the MIX model to predict D2cc for the organs-at-risk with an error <5%. While clearly specific to clinical practice, the model can be used in the development of quality assurance tools to identify treatment plans with sub-optimal sparing of the organs-at-risk. It can also be used to improve pre-planning and in the development of real-time intra-operative planning tools.

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